I think you’re thinking of levenstein distance (the number of modifications required to transform one string into the other string) 
It’s super great if your database has multiple similar entries you want to match to the same entry, like “John doe” an “John Doe” (difference is the D)
Me too! But it depends on the type of data. I thought I could do the same for finding keywords in the transcripts from the Dev-Day keynote for the Bingo event thing.
Oh boy was I wrong, and I had a lot of false positives, luckily @curt.kennedy came to the rescue with an alias function to replace the fuzzy matching one, ond that worked perfectly 
Thank you for sharing your findings with us! I’m very interested in seeing where this goes!
No, and welcome to the community, by the way. PDFs are listed as a supported file type, so there’s nothing wrong with trying, but I would recommend that you try asking GPT to convert your PDFs into Markdown and see what comes out at the other end. That will give you an idea of how successful GPT is at reading them.